Technology exists for recommending products to customers. For example, technology exists to recommend a movie to a customer based on an understanding of what movies the customer previously enjoyed, and based on classifying the customer with other moviegoers of similar movie taste.
The above-described technology for recommending products is for the most part based on historical information indicating the customer's preferences. Thus, recommendations of products that are drastically dissimilar to products the customer has previously enjoyed will not be made. Moreover, there are certain categories of products where a customer's history is not a good indicator of what products a customer would like. For example, consider the case where product is being purchased based on its aesthetic qualities. An example of such a product is an item of furniture. In this case, the customer's historical preferences with regard to items of furniture may not be a good indicator of whether the customer will like a particular piece of furniture even if said piece of furniture is similar to items of furniture that the customer has previously liked. Thus, for products where purchasing is driven by aesthetics, it is important to show a customer different products and to engage the customer in a discovery process in order to uncover products that the customer would like.